• DocumentCode
    1032810
  • Title

    Efficiency of resource brokering in grids for high-energy physics computing

  • Author

    Crosby, Paul ; Colling, David ; Waters, David

  • Author_Institution
    Dept. of Phys. & Astron., Univ. Coll. London, UK
  • Volume
    51
  • Issue
    3
  • fYear
    2004
  • fDate
    6/1/2004 12:00:00 AM
  • Firstpage
    884
  • Lastpage
    891
  • Abstract
    This paper presents a study of the efficiency of resource brokering in a computational grid constructed for CPU and data intensive scientific analysis. Real data is extracted from the logging records of an in-use resource broker relating to the running of Monte Carlo simulation jobs, and compared to detailed modeling of job processing in a grid system. This analysis uses performance indicators relating to how efficiently the jobs are run, as well as how effectively the available computational resources are being utilized. In the case of a heavily loaded grid, the delays incurred at different stages of brokering and scheduling are studied, in order to determine where the bottlenecks appear in this process. The performance of different grid setups is tested, for instance, homogeneous and heterogeneous resource distribution, and varying numbers of resource brokers. The importance of the speed of the grid information services (IS) is also investigated.
  • Keywords
    Monte Carlo methods; grid computing; high energy physics instrumentation computing; information services; processor scheduling; resource allocation; CPU; Monte Carlo simulation; computational grid; computational resources; data intensive scientific analysis; distributed computing; grid information service; heavily loaded grid; heterogeneous resource distribution; high-energy physics computing; homogeneous resource distribution; job processing; logging record; performance indicators; resource brokering efficiency; resource management; resource scheduling; Data analysis; Europe; Grid computing; Large-scale systems; Middleware; Physics computing; Resource management; Scheduling; Testing; Water resources; Distributed computing; grid; performance indicators; resource management;
  • fLanguage
    English
  • Journal_Title
    Nuclear Science, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9499
  • Type

    jour

  • DOI
    10.1109/TNS.2004.829575
  • Filename
    1311986